scholarly journals Body composition indices and cardiovascular risk in type 2 diabetes. CV biomarkers are not related to body composition

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 309-316 ◽  
Author(s):  
Aleksandra Markova ◽  
Mihail Boyanov ◽  
Deniz Bakalov ◽  
Adelina Tsakova

AbstractBackgroundThis study aims to explore the correlations of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and body composition with levels of asymmetric dimethylarginine (ADMA), endothelin 1(ET-1), N-terminal brain natriuretic pro-peptide (NT-proBNP) and calculated cardiovascular risks.Methods102 women and 67 men with type 2 diabetes participated. Serum levels of NT-proBNP were measured by electro-hemi-luminescence while ELISA were used for ADMA and ET-1. Cardiovascular risks were calculated using the Framingham Risk Score (FRS), the UKPDS 2.0 and the ADVANCE risk engines. Statistical analysis was performed on an IBM SPSS 19.0.ResultsThe BMI outperformed all other indices of obesity (WC, WHtR, WHR), as well as body composition parameters (body fat%, fat mass, fat free mass and total body water) in relation to the estimated risks for coronary heart disease and stroke, based on different calculators. The correlations of the obesity indices with the serum cardiovascular biomarkers were not significant except for BMI and fat mass versus ET-1, and for fat free mass and total body water versus ADMA.ConclusionsThe WC, WHR, WHtR, BF%, FM and FFM apparently do not add significant information related to the levels of cardiovascular biomarkers or the calculated CV-risks.

Author(s):  
Ikuro Matsuba ◽  
Masahiro Takihata ◽  
Masahiko Takai ◽  
Hajime Maeda ◽  
Akira Kubota ◽  
...  

2001 ◽  
Vol 86 (9) ◽  
pp. 4161-4165 ◽  
Author(s):  
Jan P. T. Span ◽  
Gerlach F. F. M. Pieters ◽  
Fred G. J. Sweep ◽  
Ad R. M. M. Hermus ◽  
Anthony G. H. Smals

In GH-deficient adults, rhGH has pronounced effects on total body water, fat free mass, and fat mass. Recently, we observed a gender difference in IGF-I responsivity to rhGH that was sex steroid dependent. The aim of the present study was to assess the effect of rhGH therapy on body composition parameters with due attention to the gender differences in biological responsiveness to rhGH. Forty-four women [36.9 ± 11.9 yr (mean ± sd)] and 33 men (37.2 ± 13.8 yr) with GH deficiency were studied every 6 months during 2 yr. The treatment goal was to achieve IGF-I levels within the age-adjusted normal range. Total body water, fat free mass, and fat mass were measured by bioimpedantiometry. To reach the treatment goal, the daily rhGH dose (IU/kg/d) had to be significantly higher in women than in men at all time intervals. During rhGH therapy, total body water and fat free mass increased significantly in both men and women (P ≤ 0.01 by ANOVA), but changes were more pronounced in men. Fat mass decreased during rhGH treatment and reached its nadir at 6 months, which was more pronounced in men than in women (P = 0.02 by ANOVA). After the initial decrease, fat mass increased again and reached baseline values after 2 yr of treatment. In both men and women, the total body water and fat free mass increases were closely related to the IGF-I increments (P < 0.001 by Pearson’s correlation test). The decrease in fat mass correlated significantly with the increase in IGF-I in men (r = −0.89, P < 0.001), not in women. Confirming our earlier data, IGF-I responsivity to rhGH was significantly higher in men than in women at all time intervals (P < 0.01 by ANOVA). Total body water and fat free mass responsivities were also higher in men than in women (P < 0.01 by ANOVA). In conclusion, gender differences in IGF-I responsivities to rhGH are accompanied by gender differences in the extent of body composition changes to rhGH. Probably because of these gender differences in IGF-I responsivity, the increases of total body water and fat free mass to rhGH replacement were greater in men than in women. Remarkably, however, in men, only total body water and fat free mass responses relative to changes in IGF-I increased during the 2 yr of rhGH therapy (P= 0.02 and 0.01, respectively, by ANOVA). In our opinion, this phenomenon might be explained by the increasing target organ sensitivity to IGF-I over time.


2018 ◽  
Vol 25 (3) ◽  
pp. 23-28
Author(s):  
Jacek Wilczyński

Abstract Introduction. The aim of the study was to assess the relationship between the body composition and postural stability of goalkeepers representing the Polish National Junior Handball Team. Material and methods. Body composition was assessed by means of bioelectrical impedance analysis. Postural stability was examined using the AccuGait AMTI force platform. Results. The body composition of the subjects was correct. All of the subjects had very good postural stability. Postural sway was higher in the sagittal plane than in the frontal one. Path Length and Average COP Speed were significantly increased during the closedeyes trial. Only Fat Mass (%) and Fat Mass (kg) were significantly directly correlated with Area Ellipse (cm2) (OE, open eyes). Inverse correlations occurred between Fat-Free Mass (kg) and Average Load Point Y (cm) (OE) as well as Average Load Point Y (cm) (CE, closed eyes). Muscle Mass (kg) was significantly inversely correlated with Average Load Point Y (cm) (OE) and also with Average Load Point Y (cm) (CE). Body Mass Index correlated negatively only with Average Load Point Y (cm) (CE). Total Body Water (kg) was significantly inversely correlated with Average Load Point Y (cm) (OE) and also with Average Load Point Y (cm) (CE). However, Total Body Water (%) only correlated negatively with Area Ellipse (cm2) (OE). Conclusions. Postural stability was determined by the composition and structure of the body. Single-sided sports specialisation can lead to static disorders of the body during the developmental period discussed. Therefore, systematic tests are needed to monitor the body composition and postural stability of handball goalkeepers.


Endocrinology ◽  
2001 ◽  
Vol 142 (11) ◽  
pp. 4813-4817 ◽  
Author(s):  
Ingrid B. Meeuwsen ◽  
Monique M. Samson ◽  
Sijmen A. Duursma ◽  
Harald J. Verhaar

1994 ◽  
Vol 71 (3) ◽  
pp. 309-316 ◽  
Author(s):  
Paul Deurenberg ◽  
Klaas R. Westerterp ◽  
Erica J. M. Velthuis-Te Wierik

Body composition was measured in nine healthy, normal-weight, weight-stable subjects in three different research centres. In each centre the usual procedures for the measurements were followed. It revealed that the measurement procedures in the three centres were comparable. Body composition was measured in each centre between 09.00 and 13.00 hours after a light breakfast by densitometry (underwater weighing) and bio-electrical impedance. A single, total-body-water determination by D2O dilution was used as a reference value. Body fat determined by densitometry was significantly lower in one centre, which, however, could be completely explained by a lower body weight, probably due to water loss (the subjects refrained for a longer time from food and drinks before the measurements in that centre) and, thus, by violation of the assumptions of Siri's (1961) formula. Also, body impedance was slightly higher in that centre, indicating a lower amount of body water. Mean body fat from densitometry was also slightly lower in that centre compared with body fat determined by D2O dilution. Individual differences between body fat from densitometry and from total body water were relatively large, up to 7% body fat. The relationship between fat-free mass from densitometry and bio-electrical impedance was not different between the centres. It is concluded that differences in the relationship between body composition and bio-electrical impedance, as reported in the literature, may be due to differences in standardization procedures and/or differences in reference population.


2021 ◽  
Vol 19 (7) ◽  
pp. 48-56
Author(s):  
Khalid Ghanim Majeed ◽  
Muthanna Hashim Dawood ◽  
Ali Khairaldeen Mohialdeen

Aim: To assess the body composition of fat mass, lean mass, visceral fat mass, and total body water in DM patients and compares their findings with a healthy control group. Material and Methods: A total of 86 people including 40 diabetes Mellitus type 2 matched for sex and age with 46 healthy control participated in the study. BMDs of the lumbar vertebrae and the hip regions like (total femur, femoral neck) were assessed using the DXA technique. The mean age of (DM) group was 59 ± 11.82 years, the height 1.55 ± 0.05 m., the weight 80.82 ± 13.25 kg, and BMI 33.81 ± 6.76 kg/m2. Results: The differences in measurements of the lumbar spine BMD (1.12 ± 0.13 g/cm2), total femur BMD (1.10± 0.17 g/cm2) neck of femur BMD (0.85± 0.35 g/cm2), and total BMD of the body (0.90± 0.06 g/cm2) were highly significant in healthy control group as compared to DM patients 0.84 ± 0.13 g/cm2, 0.99±0.15 g/cm2, 0.82± 0.24 g/cm2 and 0.79 ± 0.09 g/cm2 respectively. Conclusion: The results shows a highly significant in the lumbar spine, total femur, and total BMC, and not significant in the neck of the femur. The total body lean compartment was not significantly different between DM patients and healthy control women groups. The total body water compartment in the DM women group was highly significant lower different comparing with a healthy control group. The mathematical equations to predict total bone density in DM type 2 and healthy control women were calculated.


Author(s):  
Ava Kerr ◽  
Gary Slater ◽  
Nuala Byrne ◽  
Janet Chaseling

The three-compartment (3-C) model of physique assessment (fat mass, fat-free mass, water) incorporates total body water (TBW) whereas the two-compartment model (2-C) assumes a TBW of 73.72%. Deuterium dilution (D2O) is the reference method for measuring TBW but is expensive and time consuming. Multifrequency bioelectrical impedance spectroscopy (BIS SFB7) estimates TBW instantaneously and claims high precision. Our aim was to compare SFB7 with D2O for estimating TBW in resistance trained males (BMI >25kg/m2). We included TBWBIS estimates in a 3-C model and contrasted this and the 2-C model against the reference 3-C model using TBWD2O. TBW of 29 males (32.4 ± 8.5 years; 183.4 ± 7.2 cm; 92.5 ± 9.9 kg; 27.5 ± 2.6 kg/m2) was measured using SFB7 and D2O. Body density was measured by BODPOD, with body composition calculated using the Siri equation. TBWBIS values were consistent with TBWD2O (SEE = 2.65L; TE = 2.6L) as were %BF values from the 3-C model (BODPOD + TBWBIS) with the 3-C reference model (SEE = 2.20%; TE = 2.20%). For subjects with TBW more than 1% from the assumed 73.72% (n = 16), %BF from the 2-C model differed significantly from the reference 3-C model (Slope 0.6888; Intercept 5.093). The BIS SFB7 measured TBW accurately compared with D2O. The 2C model with an assumed TBW of 73.72% introduces error in the estimation of body composition. We recommend TBW should be measured, either via the traditional D2O method or when resources are limited, with BIS, so that body composition estimates are enhanced. The BIS can be accurately used in 3C equations to better predict TBW and BF% in resistance trained males compared with a 2C model.


Author(s):  
Keisuke Shiose ◽  
Emi Kondo ◽  
Rie Takae ◽  
Hiroyuki Sagayama ◽  
Keiko Motonaga ◽  
...  

Bioimpedance spectroscopy (BIS) is an easy tool to assess hydration status and body composition. However, its validity in athletes remains controversial. We investigated the validity of BIS on total body water (TBW) and body composition estimation in Japanese wrestlers and untrained subjects. TBW of 49 young Japanese male subjects (31 untrained, 18 wrestlers) were assessed using the deuterium dilution method (DDM) and BIS. De Lorenzo’s and Moissl’s equations were employed in BIS for TBW estimation. To evaluate body composition, Siri’s 3-compartment model and published TBW/fat-free mass (FFM) ratio were applied in DDM and BIS, respectively. In untrained subjects, DDM and BIS with de Lorenzo’s equation showed consistent TBW estimates, whereas BIS with Moissl’s equation overestimated TBW (p < 0.001 vs. DDM). DDM and BIS with de Lorenzo’s equation estimated FFM and percent of fat mass consistently, whereas BIS with Moissl’s equation over-estimated and under-estimated them (p < 0.001 vs. DDM). In wrestlers, BIS with de Lorenzo’s and Moissl’s equations assessed TBW similarly with DDM. However, the Bland–Altman analysis revealed a proportional bias for TBW in BIS with de Lorenzo’s equation (r = 0.735, p < 0.001). Body composition assessed with BIS using both equations and DDM were not different. In conclusion, BIS with de Lorenzo’s equation accurately estimates the TBW and body composition in untrained subjects, whereas BIS with Moissl’s equation is more valid in wrestlers. Our results demonstrated the usefulness of BIS for assessing TBW and body composition in Japanese male wrestlers.


2010 ◽  
Vol 2010 ◽  
pp. 1-4 ◽  
Author(s):  
H. Gin ◽  
V. Rigalleau ◽  
C. Perlemoine

Aims.To determine the progression of body weight (BW) and body composition (BC) in patients with type 2 diabetes mellitus (T2D) on insulin therapy and the consequences on muscle strength (MS) as a reflect of free fat mass increases.Research design and methods.We analysed BC using air displacement plethysmography and MS by hand grip dynamometry in 40 T2D before and after three (M3) and six months (M6) of insulin therapy.Results.at baseline HbA1c was 9.76±1.6% and BW was stable with fat mass (FM) 28±10.7 kg; and fat free mass (FFM) 52.4±11 kg; at M6, HbA1c improved to 7.56±0.8%; insulin doses tended to increase. BW gain at M6 was+3.2±4.2 kg and with an increase of only 25% by M3; it was composed of FM, whereas FFM was unchanged. MS did not increase on insulin therapy.Conclusions.In T2D, BW gain was composed exclusively of FM with no improvement in MS.


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